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Research on Extraction Method for Taxonomic Relation among Conceptions of Tea-science Field Ontology
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作者 童波 《Agricultural Science & Technology》 CAS 2010年第11期180-182,共3页
[Objective] Taking the knowledge of tea-science field as research object,an extraction method for the taxonomic relation of ontology conception was proposed in the paper.[Method] Through improving the rule based on la... [Objective] Taking the knowledge of tea-science field as research object,an extraction method for the taxonomic relation of ontology conception was proposed in the paper.[Method] Through improving the rule based on language mode,generalized suffix tree was constructed for the concept set of tea-science field,forming hierarchical structure and taxonomic relation among conceptions.[Result and Conclusion] Moreover,corresponding prototype system was developed based on above method,and test result indicating that the method was effective. 展开更多
关键词 Tea-science field ontology Conception Taxonomic relation generalized suffix tree
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Discovering User Profiles for Web Personalized Recommendation 被引量:2
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作者 Ai-BoSong Mao-XianZhao +2 位作者 Zuo-PengLiang Yi-ShengDong Jun-ZhouLuo 《Journal of Computer Science & Technology》 SCIE EI CSCD 2004年第3期320-328,共9页
With the growing popularity of the World Wide Web, large volume of useraccess data has been gathered automatically by Web servers and stored in Web logs. Discovering andunderstanding user behavior patterns from log fi... With the growing popularity of the World Wide Web, large volume of useraccess data has been gathered automatically by Web servers and stored in Web logs. Discovering andunderstanding user behavior patterns from log files can provide Web personalized recommendationservices. In this paper, a novel clustering method is presented for log files called Clusteringlarge Weblog based on Key Path Model (CWKPM), which is based on user browsing key path model, to getuser behavior profiles. Compared with the previous Boolean model, key path model considers themajor features of users'' accessing to the Web: ordinal, contiguous and duplicate. Moreover, forclustering, it has fewer dimensions. The analysis and experiments show that CWKPM is an efficientand effective approach for clustering large and high-dimension Web logs. 展开更多
关键词 web log user profile PERSONALIZATION generalized suffix tree CLUSTERING
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